Data Scientist / Data Analytics Consultant at Fiverr International Ltd
Consultant
Top 10
Jul 14, 2026
I have not utilized Cube's pre-aggregation feature, but I have studied how to build decision trees from parent to child leaves. I understand how it is structured with two branches, three branches, and so on. I have worked on that aspect as well concerning decision trees. From the functionality perspective, at this moment, I do not think there are any missing features in Cube that I would want to see included in the next release. Perhaps some features could be added depending on specific working conditions. Given my experience with Cube, I would advise organizations to prioritize managing hierarchies when developing Cube, as hierarchies are vital for efficient data retrieval. The hierarchy resembles a tree structure with parent, child, and then child leaf, and it essentially continues. If I manage these hierarchies effectively, it greatly facilitates retrieving the specific data and records I need in an efficient and timely manner. Overall, I would rate this product a 7.5 out of 10.
Senior Analytics Engineer at a tech vendor with 501-1,000 employees
Real User
Top 5
May 12, 2026
There is something that should be improved. We are providing metrics on email, and in the email industry we have both transactional emails and marketing emails. We have different models for these, but the metrics are actually the same: open rates, deliverability rates, soft bounce rates, and other metrics. There is no way to create a real template that is not exposed directly in the UI. We basically customized it by creating a file for all the metrics, and then we extended our previous views with this template. However, this template is exposed directly in the UI, which is not relevant for us. We do not want people using the UI and selecting metrics from this template. One thing that would be really helpful using Cube would be to have the ability to generate charts directly and embed them inside our app. I would say we could quit Omni for this kind of feature. I would recommend starting with a use case directly, using Docker, and putting it up and running really quickly. Then plug a source. Do not plug many sources at the very beginning. Just try it, check the value proposition, and I am pretty sure you will be amazed in no time. Identify a pain point and try to tackle it with Cube. Once you have done this step, you are pretty much committed to the solution because it works. I would rate my overall experience with this solution as nine out of ten.
Project manager at a consultancy with 51-200 employees
Real User
Top 10
May 6, 2026
My experience with pricing, setup cost, and licensing for Cube was good and it helped me a great deal in analyzing the pricing. I believe Cube's relationship with my company is as a reseller. My overall review rating for this product is 8.
Analytics Engineer at a tech vendor with 501-1,000 employees
Real User
Top 5
May 6, 2026
Understanding Cube's capabilities and adapting organizational data philosophies are imperative. Initial adoption should focus on building a minimum viable semantic layer, consolidating key metrics into a single source of truth to showcase the tool's value. Budget constraints dictate the choice between open source or cloud implementations. I would rate this product an eight out of ten.
Cube is well-suited to help save time on financial reporting if you need to refresh the same templates each month. It is also great for building templates and pulling in data directly from Excel or Google Sheets. However, it is less appropriate for companies that run into issues with uploading large sets of transaction data, and it does not have robust planning or forecasting features that you will find in other FP&A tools competitors. I would rate this product a 9 out of 10.
Cube offers a dynamic business intelligence platform tailored for efficient data transformation and analytics. Engineered for scalability and performance, Cube adapts to complex data environments, enhancing data accessibility and operational insights.Cube facilitates seamless integration into existing data ecosystems, bringing enhanced data processing capabilities to businesses. Utilized by companies seeking streamlined analytical processes, Cube's architecture supports custom data...
I have not utilized Cube's pre-aggregation feature, but I have studied how to build decision trees from parent to child leaves. I understand how it is structured with two branches, three branches, and so on. I have worked on that aspect as well concerning decision trees. From the functionality perspective, at this moment, I do not think there are any missing features in Cube that I would want to see included in the next release. Perhaps some features could be added depending on specific working conditions. Given my experience with Cube, I would advise organizations to prioritize managing hierarchies when developing Cube, as hierarchies are vital for efficient data retrieval. The hierarchy resembles a tree structure with parent, child, and then child leaf, and it essentially continues. If I manage these hierarchies effectively, it greatly facilitates retrieving the specific data and records I need in an efficient and timely manner. Overall, I would rate this product a 7.5 out of 10.
There is something that should be improved. We are providing metrics on email, and in the email industry we have both transactional emails and marketing emails. We have different models for these, but the metrics are actually the same: open rates, deliverability rates, soft bounce rates, and other metrics. There is no way to create a real template that is not exposed directly in the UI. We basically customized it by creating a file for all the metrics, and then we extended our previous views with this template. However, this template is exposed directly in the UI, which is not relevant for us. We do not want people using the UI and selecting metrics from this template. One thing that would be really helpful using Cube would be to have the ability to generate charts directly and embed them inside our app. I would say we could quit Omni for this kind of feature. I would recommend starting with a use case directly, using Docker, and putting it up and running really quickly. Then plug a source. Do not plug many sources at the very beginning. Just try it, check the value proposition, and I am pretty sure you will be amazed in no time. Identify a pain point and try to tackle it with Cube. Once you have done this step, you are pretty much committed to the solution because it works. I would rate my overall experience with this solution as nine out of ten.
My experience with pricing, setup cost, and licensing for Cube was good and it helped me a great deal in analyzing the pricing. I believe Cube's relationship with my company is as a reseller. My overall review rating for this product is 8.
Understanding Cube's capabilities and adapting organizational data philosophies are imperative. Initial adoption should focus on building a minimum viable semantic layer, consolidating key metrics into a single source of truth to showcase the tool's value. Budget constraints dictate the choice between open source or cloud implementations. I would rate this product an eight out of ten.
Cube is well-suited to help save time on financial reporting if you need to refresh the same templates each month. It is also great for building templates and pulling in data directly from Excel or Google Sheets. However, it is less appropriate for companies that run into issues with uploading large sets of transaction data, and it does not have robust planning or forecasting features that you will find in other FP&A tools competitors. I would rate this product a 9 out of 10.